app.py

import streamlit as st
from transformers import pipeline
from gtts import gTTS
from pytube import Search
import os

# Initialize conversational model for empathetic dialogue
conversational_bot = pipeline("text-generation", model="microsoft/DialoGPT-medium")

# Initialize sentiment analysis
sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

# Set up Streamlit page
st.set_page_config(page_title="Grief and Loss Support Bot", page_icon="🌿", layout="centered")
st.markdown("""
    <style>
    .css-1d391kg { background-color: #F3F7F6; }
    .css-ffhzg2 { font-size: 1.5em; font-weight: 500; color: #4C6D7D; }
    .stTextInput>div>div>input { background-color: #D8E3E2; }
    .stButton>button { background-color: #A9D0B6; color: white; border-radius: 5px; }
    .stButton>button:hover { background-color: #8FB79A; }
    .stTextInput>div>label { color: #4C6D7D; }
    </style>
""", unsafe_allow_html=True)

# Title
st.title("Grief and Loss Support Bot 🌿")
st.subheader("Your compassionate companion in tough times 💚")

# Get user input
user_input = st.text_input("Share what's on your mind...", placeholder="Type here...", max_chars=500)

# Store previous response to check for repetition
if 'previous_response' not in st.session_state:
    st.session_state.previous_response = ""

# Check if user has entered text
if user_input:
    # Run sentiment analysis to check for distress
    sentiment = sentiment_analysis(user_input)[0]

    # Generate empathetic response with increased length and more context
    response = conversational_bot(user_input, max_length=300, temperature=0.9, top_k=50, num_return_sequences=1)

    # Choose the response that does not repeat what the user said
    best_response = response[0]['generated_text']

    # Ensure the response is supportive and does not repeat the user's input
    if user_input.lower() in best_response.lower():
        best_response = "I understand how you're feeling. You're not alone in this. I'm here to listen and help."
    
    # Store the response for future comparison
    st.session_state.previous_response = best_response

    # Display response
    st.text_area("Bot's Response:", best_response, height=250)

    # Text-to-speech output
    tts = gTTS(best_response, lang='en')
    audio_file = "response.mp3"
    tts.save(audio_file)
    st.audio(audio_file, format="audio/mp3")

    # Suggest a productive activity based on detected keywords
    if any(keyword in user_input.lower() for keyword in ["lonely", "lost", "sad"]):
        st.info("Here's a suggestion to help you cope:")
        hobbies = ["journaling", "yoga", "painting"]
        activity = st.selectbox("Choose an activity you'd like to try:", hobbies)
        
        # Search YouTube for videos related to the selected activity
        search = Search(activity)
        search_results = search.results[:3]  # limit results to 3 videos
        for video in search_results:
            st.write(f"[{video.title}]({video.watch_url})")

    # Crisis resources
    crisis_keywords = ["help", "suicide", "depressed", "emergency", "hurt", "lost"]
    if any(keyword in user_input.lower() for keyword in crisis_keywords):
        st.warning("It seems like you might be in distress. Please reach out to a crisis hotline or a trusted individual.")
        st.write("[Find emergency resources here](https://www.helpguide.org/find-help.htm)")